JPH10134173A - Generation and process of image data - Google Patents

Abstract

PROBLEM TO BE SOLVED: To represent both low-space-resolution information and highspace- resolution information in a single image by representing the low-space-resolution information by color variation and the highspace-resolution information by lunminance variation. SOLUTION: To discriminate, label, or feature various areas of an image for perceptual processing by a human visual sensation system, pixels to be changed in an image are determined (step 200). Then a new color to be given to those pixels is also determined (step 202). Then the color of proper pixels is changed to the new color and pixel data are changed so as to scale the luminance with a uniform coefficient (step 204). At this time, the system use an RGB formula as to the new color and proper values of red, green, and blue of the new color needed to generate proper pixel luminance of each pixel are calculated. Consequently, the high-space-resolution information shown in the form of luminance variation can be held.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] The present invention relates to the field of processing data representing digitized images. The present invention addresses the problem of providing images that simultaneously represent both high and low spatial resolution information related to a common subject.

[0002]

2. Description of the Related Art A digitized image is an image represented in a digital data format. Generally, a digitized image is represented in a "rasterized" or "bit map" format, and the value of each pixel of the image is individually represented in the data in that format. In the case of a monochrome image, each pixel can be represented by data indicating its luminance on a gray scale ranging from black (no luminance) to white (maximum luminance). Thus, a typical monochrome image data file can include one byte for each pixel, providing a range of 256 brightness values for each pixel. "Color"
In the case of an image, each pixel can be represented by data indicating the value of its respective red, green, blue (RGB) component. For example, the image may be represented in a "24-bit" data format that includes one byte for each of the RGB components of each pixel, thereby providing a range of over 16 million pixel values. Gray scale pixels in an RGB image are typically characterized by equal red, green, and blue values.

A pixel of a color image may be characterized by data representing its hue, saturation, and brightness (HSV) components. In HSV systems and similar rendering systems, the hue component indicates the color of the pixel, the chroma component indicates the relative amount of the pixel's color and grayscale value, and the lightness component indicates the intensity or brightness of the pixel. Various formulas are known for converting an RGB pixel representation to an equivalent HSV representation.

If it is desired to reduce the amount of data required to represent a color image, the pixels of the image can be represented by data associated with a color map. For example, consider an image represented in 24-bit color. Each pixel of the image can have any one of more than 16 million possible values, but this color gamut requires 3 bytes of storage for each pixel. However, using known processes, it is possible to construct a histogram of the pixels of an image such that a smaller number of colors best represent the colors of the image, and a color map containing only those colors can be constructed. Can be built. Thereafter, a modified image containing only the colors of the color map can be constructed. This modified image is a color image stored in the form of a color table.
It can be represented as pixel data in the form of a reference to an item on the map. Therefore, if the color map is 25
When including six colors, each pixel of the image can be represented as a single byte reference to an entry in the color table, rather than as a three byte RGB representation.

The colors that can be displayed on known display devices, such as printers and video displays, vary in their dynamic range, ie, the maximum potential brightness of each color. The dynamic range of a color is determined in part by the display device. One approximation commonly used to determine the brightness of one pixel of an RGB image is described by the formula L = 0.3 (R) +0.6 (G) +0.1 (B). It will be seen that, with this approximation, the green component G of the image provides a higher luminance than the red component R and significantly higher luminance than the blue component B. Also, the colors in the green range of the display spectrum are about twice the dynamic range of the colors in the red range of the spectrum, and about six times the dynamic range of the colors in the blue range of the spectrum. Can be inferred from this approximation.

For the processing of digitized images, a set of high spatial resolution information, eg, geographic features of land masses,
It has been found that it may be desirable to provide a set of low spatial resolution information related to the first set of information, for example, images representing both regions of the land mass having a given temperature. Current methods for providing such images are:
Providing an image created from the first set of information;
Then, replacing multiple regions of the image with a representation created from the second set of information. Thus, using the above example, an image of a geographic feature can be generated from the geographic data. Thereafter, areas having a temperature within a given range can be replaced in the image by a representation indicating a temperature region of interest, for example, a uniform color. In current technology, a user of a computer system can define the area of the image to be changed by using a pointing device such as a mouse, and the movement of the mouse indicates the boundary of the area to be changed.

[0007]

SUMMARY OF THE INVENTION Applicants have recognized that a set of high spatial resolution information and a set of high spatial resolution information related to a common subject matter.
The current practice of digital image processing to provide images that represent both sets of low spatial resolution information is to optimize the characteristics of the images to convey information according to the physiological attributes of the viewer. Can not. Magnocellula pathway that accepts visual information presented as color changes
It is well known in the art of neurophysiology that the receptivity of the visual information decreases as the spatial resolution (ie, detail) of the visual information increases. Thus, when the visual information becomes very detailed, it becomes less and more effective to express the change in information by changing the color of the image. However, the parvocellular path
way) accepts changes in luminance even when the spatial resolution is high. As a result, the applicant has determined that it is preferable to present very detailed information by a change in luminance. Thus, the present invention generally provides a simultaneous visual representation of multiple sets of related information, such that low spatial resolution information is presented by color changes and high spatial resolution information is presented by luminance changes. Including.

[0008]

SUMMARY OF THE INVENTION To illustrate a method of using the present invention, a first set of information describing very detailed geographic features of a land mass and a less detailed surface temperature gradient in the mass. Let us consider the case where it is necessary to generate an image from the second set of information representing According to current technology, two images are generated. The first image presents geographic information. The second image includes a terrain image with sections replaced by colors to represent temperature. These images are placed side by side so that the viewer can compare them.

[0009] In contrast, the present invention improves upon known method techniques by generating an image that provides a simultaneous representation of high spatial resolution information and low spatial resolution information in a single image.
In the present invention, each pixel of a computer-generated image is treated as having a value consisting of two components, color and luminance. The color value represents the hue and saturation of the pixel, and the luminance value represents the perceived brightness of the pixel.
In general, the objects of the invention are achieved by representing low spatial resolution information by color change and high spatial resolution information by luminance change. When practicing the present invention to modify high spatial resolution image data in response to corresponding low spatial resolution information, this process is sometimes referred to as a "color wash".

The present invention can be used in various applications and embodiments. 24-bit high spatial resolution information
Consider images represented in color. According to the present invention,
Pixels in the region of interest resulting from a set of related low spatial resolution information are represented by the color change to represent the low spatial resolution information, but retain the relative luminance contrast representing the high spatial resolution information. Is redefined. Relative luminance contrast can be stored in several ways. For example, if the dynamic range of the selected color allows, the luminance values of the pixels can be saved as well. Alternatively, the luminance values of the pixels in the region can be scaled to preserve the relative luminance contrast of the original representation of the image, but to span the full dynamic range of the selected color. However, if the dynamic range of the selected color is less than the dynamic range of the pixels in the region of interest or of the entire image, then first the area of interest or the entire image should be matched to match the selected dynamic range. The intensity of any pixel can be scaled. Alternatively, the pixels of the region of interest can be redefined to have a selected color, and have a luminance proportional to the luminance from the original representation image. These methods can be used for multiple regions and multiple colors as well. However, in each case, it is preferable to use the same dynamic range throughout the image. Therefore,
It is often necessary to scale the luminance value of each pixel in the entire image so that the dynamic range of the image matches the dynamic range of the selected color having the smallest dynamic range.

Thus, the present invention can be implemented in a method for processing data representing an image. In a first embodiment, the method generally comprises determining the pixels to be changed in the image and their expected colors, changing the pixels to a selected color, and Altering the image data to have a luminance proportional to the luminance of the original representation of. The method can further include determining a maximum luminance for the color. If the dynamic range of the selected color is sufficient, the pixel can be given the same brightness as the original representation of the image. Alternatively, the brightness of the changed pixels can be scaled such that the highest brightness within the dynamic range of the selected color is proportional to either the highest brightness between the changed pixels or the highest brightness of the entire image. If the dynamic range of the selected color is smaller than the dynamic range of either the area to be changed or the entire image, scale the pixel or the entire image to be changed, respectively, to match the dynamic range of the selected color This allows the image to be changed first. In a similar embodiment of the invention, means for performing the method and computer program product means for programming a computer to perform the method may be included.

[0012] The present invention can be further implemented in a second alternative method for processing image data, the method being optimized to perform multiple color changes simultaneously, and to the unaltered portion of the image. Can be further optimized to produce a final image such that the dynamic range of the image does not exceed the dynamic range of the changed portion of the image.
This method generally involves changing which pixels of the image
Determining the plurality of colors to be changed, determining the maximum brightness of each of these colors,
Determining the minimum of these maximum luminances. Thereafter, the maximum pixel intensity of the original representation of the image is determined, and if this is greater than the minimum of the maximum color intensity, the dynamic color of the changed color having the minimum dynamic range is determined.
The image is scaled proportionally to have a new dynamic range equal to the range. Then change the appropriate pixels in the image to each new color,
Assign proportional brightness. The brightness of each pixel can be equal to the brightness before the color change, or it can be scaled to use the full dynamic range of the color being changed. In a similar embodiment of the invention, means for performing the method and computer program product means for programming a computer to perform the method may be included.

[0013]

DETAILED DESCRIPTION OF THE INVENTION The present invention generally includes systems, methods, and products for generating and processing image data. FIG. 1 illustrates, in general form, an example system for generating and processing image data capable of implementing the present invention. Generation and processing of image data is typically performed by computer system 100. The system includes an image acquisition device 1 such as a data storage device 102 or a camera.
04 can receive image data. The system receives input via an input device 106, such as a mouse, and displays an image on a display device 108, such as a video display terminal.

Computer system 100 includes various data, modules, processes, and inputs. The processing of the image data performed by the computer system 100 is performed by the color wash module 110. Color wash module 11
0 manipulates input 112 from the system user and "raw" data 116 or image data. The image data may be provided as a processed image data file 114 generated by the image processing module 118 or may be provided as a direct output of the image processing module 120. The color wash module generates the color-washed image data 122.

Therefore, the present invention can be implemented in the system shown in FIG. Further disclosure of the present invention is presented in the following three sections. In the first section, image data is used to identify, label, or characterize various regions of an image in a manner optimized for perceptual processing by the human visual system. A method for processing is disclosed. The second section discloses a method of color selection for presentation of low spatial resolution information. The third section discloses a method for generating an image representing a single set of high spatial resolution information and multiple sets of low spatial resolution information.

I. Processing Image Data According to the Present Invention This section aims to use color to identify, label, or characterize various regions of an image in a manner optimized for perceptual processing by the human visual system. Handles the processing of image data.

Referring to FIG. 2, there is shown a first example of a processing flow in an image processing system such as FIG. 1 for processing image data according to the present invention. For the purpose of discussing FIG. 2, it can be assumed that the data processing operation in question involves processing images representing high spatial resolution information stored in a single data file in a 24-bit format. However, this method, for example, has a red
The present invention can be similarly applied to other storage formats of rasterized data, such as data stored in three individual files including green and blue components, or data stored in the HSV format.

The method illustrated in FIG. 2 represents a first type of operation that can be performed on image data according to the present invention. Specifically, this operation involves assigning a color to one region of the image such that the luminance value of each pixel in the region after coloring is the same as the luminance value before coloring. However, it should be noted that this operation can be performed by assigning a color to one area of the monochrome image or making one area of the color image monochrome.

Referring specifically to FIG. 2, at 200,
First, the pixels to be changed in the image are determined. Such a determination of the pixel can be made in various ways. For example, a user of the system can use an input device such as a mouse to indicate the area to be changed. Then, a known process can be invoked to determine the pixels that fall within the indicated area. Alternatively, a second data file containing low spatial resolution information associated with the image can be referenced. For example, an area of the image to be changed can be determined with reference to a second file that stores temperature data for the area represented in the image to indicate a temperature within a particular range.

In addition to determining which pixels to change, the system must also determine at 202 a new color to be assigned to these pixels. This can be determined from user input indicating the appropriate color. Alternatively, an appropriate color can be designated by referring to a reference table such as a table indicating an appropriate display color for each part of the image indicated to be within a specific temperature range.

After determining the pixel to change and its new color, the system changes the color of the appropriate pixel to the new color at 204 and changes the pixel data to scale its brightness by a uniform factor. I do. The way to do this can vary depending on the attributes of the image and the color selected. In a first example, consider an image in which the dynamic range of the image is 0-0.9 and the dynamic range of the pixels to be changed is 0-0.75. When the dynamic range of the new color is also 0 to 0.75, that is, the maximum luminance value (hereinafter max (L _color )) of the _color is 0.
If 75, the pixels can be modified to preserve the brightness of the original representation of the image. Therefore, the system uses the RGB formula for the new color,
The appropriate values for the new colors red, green, and blue needed to generate the appropriate pixel luminance (hereinafter L _pixel ) for each pixel can be easily calculated. Thus, it can be said that the pixels are scaled by a uniformity factor of about one. Those skilled in the art will appreciate that this scaling factor is not completely uniform, but rather uniform, as the system must choose from the available individual colors. Therefore, the scaling factor will fall approximately within a known and quantifiable range. Scaling can be done by real-time processing of the pixel data using a scaling formula, or by reference to a lookup table that associates luminance values with RGB color formulas.

If the color selected to modify one region cannot reproduce the full dynamic range of the region using it, an alternative processing method can be used. In such a case, reducing the dynamic range of the entire image before changing the region may be such that the dynamic range of the pixels in the region to be changed matches the dynamic range of the color in which it is changed. It may be desirable. For example, consider the above example, with the change that the dynamic range of the new color is 0-0.7. This range covers the entire image (0.
9) and the pixels of the image to be modified (0.75). Therefore, in order to reduce the dynamic range of the entire image to the dynamic range of the new color whose area is changed, all pixels of the image are scaled by a factor of approximately max ( _Lcolor ) / max ( _Lpixel ). be able to. As a result, when the pixel color is changed, its luminance value can be kept at the same value as the luminance value of the scaled image before the color change.

As an alternative to the processing method described above,
It may be desirable to change that region of the image so that the relative pixel brightness of one region is maintained within that region, but is no longer proportional to the rest of the image. For example, the dynamics of pixels in that region of the original image
One region of the image can be modified to have a color with a dynamic range smaller than the range. In this case, the pixels can be modified to retain their relative brightness, but the region should have a smaller dynamic range than that of the original image. Thus, the region has a reduced ability to represent high spatial frequency information. Similarly, the region is the dynamic image of the region in the original image.
It can be modified to have colors with a dynamic range greater than the range. In this case, the pixels can be modified to retain their relative brightness, but the area should have a dynamic range that is greater than the dynamic range of the area in the original image. Thus, the ability of that region to represent high spatial frequency information is enhanced.

To continue the above example, next, the color max (L _color ) given to the area to be changed is 0.9.
Consider the case of 5. Therefore, its color is
It has a larger dynamic range than both the area to be changed (0.75) and the whole image (0.9). The system can scale the intensity of each pixel in the region such that a larger dynamic range is presented in the region than the original representation of the image. In such a case, the brightness of each pixel is m
ax (L _color ) / max (L _pixel )
(L _pixel ) is either the highest luminance value of the pixel to be changed or the highest luminance value in the entire image. In the former case, the result is that the pixel with the highest luminance (0.75) of the pixels to be changed is changed to have the highest luminance of the new color (0.95), and all other changes are made. Of pixels become proportionally brighter. In the latter case, the result is that the pixel with the highest luminance of the pixels to be changed has the relative luminance that it would have if the dynamic range of the entire image was the dynamic range of the new color To be changed. If the selected color has a dynamic range that is smaller than the dynamic range of the area of the original representation to be changed, the same scaling factor can be applied.

Therefore, from the above example, the color selection of the area to be changed is determined by the desired dynamic color of the area after the change.
You can see that this can be done depending on the range.
If it is necessary to reduce the ability of the modified region to represent high spatial frequency information, a color having a dynamic range smaller than the original dynamic range of the region can be selected. If it is necessary not to affect the ability of the modified region to represent high spatial frequency information, selecting a color with a dynamic range equal to or greater than the unmodified dynamic range of that region it can. If the dynamic range of the selected color is larger than the dynamic range of the area to be changed, the former dynamic
Only the part of the range that matches the dynamic range of the region before the change is used. If it is necessary to enhance the ability of the modified region to represent high spatial frequency information, a color having a dynamic range that is greater than the dynamic range of the region before the modification can be selected. In such a case, the relative brightness of each pixel will be increased by a uniformity factor so that the pixels use the full dynamic range of the new color.

In some applications, it may be desirable to modify multiple regions of the image and use multiple new colors to represent each modified region independently. For example, 1
It may be desirable to color the entire satellite image using a different color to match the 0 degree temperature increment. For the purposes of this discussion, the pixels of the overall image have a dynamic range of 0-0.9, the pixels of the first region of the image have a dynamic range of 0-0.8, Modified to be a color having a dynamic range of 0.6, wherein the pixels in the second region of the image have a dynamic range of 0 to 0.75;
Consider the case where the color is changed so as to have a dynamic range of 0 to 0.7. FIG. 3 shows an example of the flow of processing in an image processing system for processing image data according to such an application example.

Referring specifically to FIG. 3, such a system determines the pixel to be changed at 300 and 30
2 determines their changed colors. This system is 3
04, the maximum luminance max (L
_colorN ) is determined, and the minimum value min (max ( _LcolorN )) of such maximum values is determined at 306. Therefore, using the numerical values in this example, the system determines that the minimum value of the maximum luminance of the pixel change color is 0.6, which is the maximum value of the pixel change color of the first region.

Next, the system determines at 308 the maximum pixel intensity max (L _pixel ) of the image and at 310 determines whether it is greater than min (max (L _colorN )). When this condition is satisfied, at least one region of pixels to be changed indicates that the dynamic range is reduced relative to the rest of the image when the change is made. Thus, at 312, the system reduces all pixels of the image to approximately min (ma
x (L _colorN)) / max change all pixel data for scaling by a factor of (L _pixel). As a result, the scaled image will have a dynamic range equal to the minimum dynamic range of the pixel's modified color.

Next, at 314, the system changes the color of the appropriate pixel to its respective new color, and changes the pixel data to scale its brightness by a uniform factor specific to that pixel's new color. . If it is necessary to maintain a uniform dynamic range over the entire image, that change can be made to approximately maintain the brightness value of each pixel, so that the brightness of each pixel scales by a factor of about 1. Is done. However, if it is necessary to maximize the luminance contrast exhibited by each new color, then the luminance value of each pixel will be max ( _LcolorN ) / max
(L _pixel ). Thus, the new color with the smallest dynamic range gives a dynamic range equal to the image dynamic range (pre-scaled to match that color's dynamic range),
Other new colors provide the dynamic range that each region would have had if the overall dynamic range of the scaled image had been the new color dynamic range of each of the changed regions.

To further discuss the process of FIG. 3, it is now assumed that the dynamic range of the two new colors is both 0-0.99, so that it is greater than the dynamic range of the original representation of the image. consider. Therefore, the system is 310 and the maximum pixel luminance max (L _pixel ) of the image is min (max
(L _colorN )) is determined to be no larger, so the appropriate pixels are changed accordingly without first scaling the entire image. As before, if it is necessary to maintain a uniform dynamic range throughout the image, the change can be made to approximately maintain the luminance value of each pixel, resulting in the luminance of each pixel Is scaled by a factor of about 1. But,
If it is necessary to maximize the brightness contrast exhibited by each new color, the brightness value of each pixel is m
It may be scaled by a factor of _{ax (L colorN) / max (} L pixel). Thus, the new colors provide the dynamic range that each region would have had if the overall image dynamic range had been the new color dynamic range of each of the changed regions.

The various alternative processes described with respect to the flowcharts of FIGS. 2 and 3 may be implemented, for example, on the computer system shown in FIG. Such an embodiment may be implemented by use of a computer program product means for programming a computer system to perform such a process. Such computer program product means may be provided as a program stored in system memory or on a storage medium independent of any system embodiment. FIG.
Computer programs programmed with the various alternative processes described with respect to the flowchart of FIG. 3 and for the purposes of the present invention are considered to include the various means necessary to perform the steps of such processes.

The embodiment of the process of FIG. 2 and its associated system and computer program product provides some alternative embodiments of the present invention, and the embodiment of the process of FIG. 3 and its associated system and computer program product is provided. Provides certain optimizations that are preferred in embodiments of the present invention, but additional embodiments are possible to those skilled in the art. For example, the process of FIG. 3 can be modified such that the relative dynamic range of the modified region is scaled to the maximum brightness of the pixels in that region, rather than the maximum brightness of the pixels in the entire image. Similarly, such a process is applicable to monochrome images and images stored in color format. Therefore, according to the present invention, various regions of a monochrome image can be colored, and various regions of a colored image can be changed to monochrome.

II. Color Selection for Presenting Low Spatial Resolution Information As mentioned above, different colors have different dynamic ranges, so in some cases, rather than providing images scaled to a single dynamic range, It may be desirable to utilize the full dynamic range of multiple colors. Thus, color selection can be affected by additional factors that suggest the desired dynamic range of the multiple colors selected to represent low spatial resolution information.

A first method for assigning colors is:
It can be based on the assignment of importance factors to each data point of low spatial resolution information. This importance factor is then used to evaluate the relative importance of each data point,
A color proportional to the importance factor can be assigned to each data point. In some cases, the importance factor may be assigned by the user. For example, consider the case where it is necessary to generate an image that presents both very detailed topographical information and less detailed information indicating areas within which it is thought to contain mineral reserves. The expected mineral output of each reserve can be entered by the user as an importance factor, which is used by the image processing system to assign the colors with the highest dynamic range to the areas assigned the highest importance. Used in. Regions with low output are assigned colors with a proportionally smaller dynamic range.

Alternatively, the system itself can assign an importance factor. For example, consider the case where it is necessary to generate an image that presents both very detailed terrain information and less detailed information indicating the county regions therein. The system can assign to each county an importance factor that represents the relative spatial resolution of the terrain data within that county region. The system assigns the color with the largest dynamic range to the area with the most detailed geographic features, so that the color selection optimizes the presentation of both fine details of terrain information and coarse details of the county area. Generates a nice image.

It may be even more desirable to use importance factors that change over time according to a set of dynamic information. For example, consider the case where it is necessary to generate an image that presents a very detailed map of an urban area and less detailed information in which an emergency has occurred. The system may assign a severity factor determined to the emergency occurrence area based on the nature of the emergency and the current state of the response thereto.
Moreover, the system can continue to reassign importance factors to each area based on updated information regarding the nature of the emergency and the current state of the reaction. Thus, the system is arranged so that the areas of greatest importance are represented by the colors with the largest dynamic range, and the color with the greater or lesser dynamic range as the importance factor changes over time. Generate a dynamic image that is reassigned.

A second method of assigning colors correlates the dynamic range of the assigned colors with the specific characteristics of the low spatial resolution information it represents. For example, consider the case where it is necessary to generate an image that presents detailed terrain information and less detailed temperature information. The system can assign a color that represents a predetermined temperature range, such that the temperature is represented by a color that has a proportional dynamic range. Thus, the system produces an image in which the lowest temperature is represented by the color with the smallest dynamic range and the highest temperature is represented by the color with the largest dynamic range. If the low spatial resolution temperature information changes over time, the system continuously updates the image and reassigns colors to areas where the temperature range has changed.

III. Method for Generating Images Representing a Single Set of High Spatial Resolution Information and Multiple Sets of Low Spatial Resolution Information For the embodiments disclosed in the previous two sections, a single set of high spatial resolution information and a single set It has been discussed in connection with an example involving a set of low spatial resolution information, eg, terrain and temperature. However, the invention is also possible with embodiments that include a single set of high spatial resolution information and multiple sets of low spatial resolution information. For example, it is necessary to generate images that show very detailed terrain information, less detailed information related to each of the county regions, and less detailed population density information within that terrain. Consider a case. The system assigns one color to each county, and within that county the colors can be varied according to population density.
Depending on the information represented, such a change can be, for example,
It can be presented in the form of gradual transitions between colors due to gradual changes in hue or saturation, or in the form of discrete transitions between colors. In addition, the method disclosed in Section II allows each district to be assigned an importance factor to select a color. The importance factor in this example can be a function of the level of detail of the terrain information and the population density information of the county.

Accordingly, the present invention generally provides a method for representing information in the form of an image by coloring regions of the image according to the low spatial resolution information and retaining the high spatial resolution information presented in the form of luminance variations. ,system,
And can be implemented in products. The present invention can further include color selection based on importance factors or other criteria that reflect additional features of the represented low spatial resolution data. The invention can also be implemented to generate an image from a set of high spatial resolution information and one or more sets of related low spatial resolution information.

Although the specific embodiments described above provide the best mode known to the inventors for carrying out the present invention, the structure and method are various, but the invention is capable of various alternative embodiments. is there. The flowcharts, hardware configurations, processes, color representation standards, and scaling techniques shown herein are exemplary. Those skilled in the art will be able to add equivalent components, methods of operation, uses, and the like, to the individually described embodiments without departing from the scope of the invention as defined in the claims. You will also notice the changes.

In summary, the following matters are disclosed regarding the configuration of the present invention.

(1) A method for processing data representing pixel values, including color and luminance values of each pixel of an image, wherein the data is modified in the image to indicate a common characteristic to be represented by the image. Determining one or more pixels to power; determining a color value to be applied to each of the one or more pixels; providing the color value to each of the one or more pixels; Altering the data representing the one or more pixel values to scale the respective luminance values of the one or more pixels by a substantially uniform factor. (2) The maximum luminance value max (L
_color ), and determining a maximum value max (L _pixel ) of the luminance of the one or more pixels, wherein the uniformity coefficient is max (L
_color ) / max (L _pixel ).
The method according to the above (1). (3) The maximum luminance value max (L
_color ) and a step of determining a maximum value max (L _pixel ) of the luminance of a plurality of pixels of the image, wherein the uniformity coefficient is max (L _color ).
/ Max (L _pixel ). The method according to the above (1), wherein (4) A system for processing data representing pixel values, including color and luminance values of each pixel of an image, wherein one to be changed in the image to indicate a common characteristic to be represented by the image. Or means for determining a plurality of pixels; means for determining a color value to be provided to each of the one or more pixels; and providing the color value to each of the one or more pixels; Means for modifying data representing the one or more pixels to scale the luminance value of each of the one or more pixels by a substantially uniform factor. (5) The maximum luminance value max (L
_color )), and means for determining a maximum value max (L _pixel ) of the luminance of the one or more pixels, wherein the uniformity coefficient is max.
( _Lcolor ) / max ( _Lpixel ). The system according to (4) above, wherein (6) The maximum luminance value max (L
_color )), and means for determining a maximum value max (L _pixel ) of the luminance of the pixels of the image, wherein the uniformity coefficient is max (L _color ).
/ Max (L _pixel ). The system according to (6) above, wherein (7) A computer program product comprising a computer usable medium having computer readable program code means therein for processing data representing pixel values, including color and luminance values of each pixel of an image. , Computer readable program code means for determining one or more pixels to change in the image to indicate a common property to be represented by the image; and providing to each of the one or more pixels Computer readable program code means for determining a color value to be obtained;
Providing the color value to each of the one or more pixels and scaling the luminance value of each of the one or more pixels by a substantially uniform factor;
Computer readable program code means for altering the data representing the one or more pixels. (8) The maximum luminance value max (L
_color ), and computer readable program code means for determining a maximum value max (L _pixel ) of the luminance of the one or more pixels, The uniformity coefficient is max (L _color ) / max
(L _pixel ). The computer program product as described in (7) above. (9) The maximum luminance value max (L
_color ), and computer readable program code means for determining a maximum value of the brightness of the pixels of the image, max (L _pixel ). Is max (L _color ) / max (L _pixel ). The computer program product according to the above (7), wherein (10) A method for processing data representing pixel values, including color and luminance values of each pixel of an image, wherein the data is modified in the image to indicate one of the common characteristics to be represented by the image. Determining one or more pixels to power; determining N color values, one for each of the one or more pixels; and a maximum for each of the N color values. Determining a luminance value max ( _LcolorN ); and a minimum value min of the maximum luminance values.
(Max (L _colorN)) determining, determining a maximum value max (L _pixel) of the luminance values of the image pixels, max (L _pixel) is min (ma
is greater than x (L _colorN)), the respective luminance values L _pixel of the image pixels min (max (L
for scaling by a factor of _{colorN)) / max (L pixel} ), and changing the data representing the pixel value of the image pixel, the color value of the N-way to each of the one or more pixels The one or more _pixels to scale the luminance value L _pixel of each of the one or more pixels by a substantially uniform factor corresponding to one of the N possible color values. Changing the data representing the value. (11) max (L _pixel ) is min (max (L
_colorN ), if not greater than the uniformity coefficient ma
characterized in that it is a _{x (L colorN) / max (} L pixel), The method according to (10). (12) max (L _pixel ) is min (max (L
_colorN )), the uniformity factor is mi
characterized in that it is a _{n (max (L colorN))} / max (L pixel), The method according to (10). (13) When max (L _pixel ) is min (max (L
_colorN )) If greater than, the uniformity coefficient is max
( _LcolorN ) / min (max ( _LcolorN )), wherein the method according to the above (10),

[Brief description of the drawings]

FIG. 1 shows, in general form, an embodiment of a system for processing image data according to the present invention.

FIG. 2 is a diagram showing a first example of a processing flow in an image processing system for processing image data according to the present invention.

FIG. 3 is a diagram showing a second example of a processing flow in an image processing system for processing image data according to a preferred embodiment of the present invention.

[Explanation of symbols]

200 Determining the pixel to be changed 202 Determining the color in which the pixel is changed 204 Changing the color and changing the pixel data to scale the luminance by a nearly uniform factor

Continued on the front page (72) Inventor John Alan Garth United States 94019 Half Moon Bay, Toulane Lane, California 94019 (72) Inventor John Timothy Robinson United States 10598 Yorktown Heights, New York North North Deerfield Avenue 3314 (72) Inventor Bernice Ellen Rogovitz USA 10562 Osiningspring Pond Road, New York 34

Claims (13)

[Claims] 1. A method for processing data representing pixel values, including color and luminance values of each pixel of an image, to be modified in said image to indicate a common characteristic to be represented by said image. Determining one or more pixels; determining a color value to be provided to each of the one or more pixels; providing the color value to each of the one or more pixels; To scale the luminance values of one or more pixels by an approximately uniform factor,
Modifying the data representing the one or more pixel values. 2. A maximum luminance value max for the color value.
(L _color ); and a maximum value max of luminance of the one or more pixels.
(L _pixel ), wherein the uniformity coefficient is max (L _color ) / max (L _pixel )
The method of claim 1, wherein 3. A maximum luminance value max for the color value.
(L _color ), and the maximum value max (L) of the luminance of a plurality of pixels of the image.
_pixel )), wherein the uniformity coefficient is max (L _color ) / max (L _pixel )
The method of claim 1, wherein 4. A system for processing data representing pixel values, including color and luminance values of each pixel of an image, the data being modified in the image to indicate a common characteristic to be represented by the image. Means for determining one or more pixels; means for determining a color value to be provided to each of the one or more pixels; and applying the color values to each of the one or more pixels. To scale the luminance value of each of the one or more pixels by a substantially uniform factor,
Means for altering the data representing the one or more pixels. 5. A maximum luminance value max for the color value.
Means for determining (L _color ), and a maximum value max of luminance of the one or more pixels.
Means for determining (L _pixel ), wherein said uniformity coefficient is max (L _color ) / max (L _pixel )
The system according to claim 4, wherein 6. A maximum luminance value max for the color value.
Means for determining (L _color ), and the maximum value max (L _pixel ) of the luminance of the pixels of the image
Means for determining the uniformity coefficient, wherein the uniformity coefficient is max (L _color ) / max (L _pixel )
7. The system according to claim 6, wherein 7. A computer comprising a computer usable medium having computer readable program code means therein for processing data representing pixel values including color and luminance values of each pixel of an image.
A program product, computer readable program code means for determining one or more pixels to change in the image to indicate a common characteristic to be represented by the image; Computer readable program code means for determining a color value to be provided to each of the pixels; and providing the color value to each of the one or more pixels; and a luminance value to each of the one or more pixels. To scale by approximately the uniform factor,
Computer readable program code means for altering the data representing the one or more pixels. 8. A maximum luminance value max for the color value.
Computer readable program code means for determining ( _Lcolor ); and a maximum value max of brightness of said one or more pixels.
Computer readable program code means for determining (L _pixel ), wherein said uniformity factor is max (L _color ) / max (L _pixel )
The computer program product according to claim 7, characterized in that: 9. A maximum luminance value max for the color value
Computer readable program code means for determining (L _color ); and a maximum value max (L _pixel ) of pixel brightness of the image.
Computer readable program for determining
Code means, wherein the uniformity coefficient is max ( _Lcolor ) / max ( _Lpixel )
The computer program product according to claim 7, characterized in that: 10. A method for processing data representing pixel values including a color value and a luminance value of each pixel of an image, the method comprising: processing an image to indicate one of the common characteristics to be represented by the image. Determining one or more pixels to be modified; determining N color values, one for each of the one or more pixels; and each of the N color values. Maximum luminance value m for
ax (L _colorN ); and a minimum value min (max (L
_colorN )) and determining the maximum value of the luminance value max of the pixel of the image
(L _pixel ); and when max (L _pixel ) is greater than min (max (L _colorN )), the luminance value L _pixel of each pixel of the image is set to min (max (L _colorN )) / max
Changing data representing the pixel values of the pixels of the image to scale by a factor of (L _pixel ); and providing one of the N color values to each of the one or more pixels. , The data representing the one or more pixel values is scaled to scale each luminance value L _pixel of the one or more pixels by a substantially uniform factor corresponding to one of the N color values. Changing. 11. When max (L _pixel ) is min (max
If (L _colorN)) no greater than, and said uniform factor is _{max (L colorN) / max (} L pixel), The method of claim 10. 12. When max (L _pixel ) is min (max
If (L _colorN)) no greater than, and said uniform factor is _{min (max (L colorN))} / max (L pixel), The method of claim 10. 13. The method according to claim 13, wherein max (L _pixel ) is min (max
( _LcolorN )), the uniformity coefficient is ma
The method according to claim 10, characterized in that x ( _LcolorN ) / min (max ( _LcolorN )).